Benchmark: set.has vs. array.includes vs in operator

Script Preparation code:

var a = [];
for (let i = 0; i < 100_000; i++) {
  a.push(i);
}
var b = new Set(a)
var c = {}
for (const key of a) {
  c[key] = 0; 
}

Tests:

includes
return a.includes(9)
lookup
return b.has(9)
in
return 9 in c

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
includes
lookup
in

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one month ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/18.3 Safari/605.1.15

Browser/OS: Safari 18 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
includes	109843160.0 Ops/sec
lookup	623569728.0 Ops/sec
in	577336896.0 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

**Benchmark Definition:**

The provided JSON represents a benchmark test that compares the performance of three different ways to check if an element exists in an array:

1. `array.includes()`
2. `set.has()`
3. `in` operator

Let's break down each option and their pros and cons:

### 1. `array.includes()`:

*   This method checks if a specified value (in this case, the number 9) exists in the array.
*   Pros:
    *   Simple to implement
    *   Widely supported by most JavaScript engines
    *   Fast performance
*   Cons:
    *   May be slower for very large arrays due to the need to iterate through each element
    *   Can be less efficient than other methods if the array is already sorted or has some other property that can be used to speed up the lookup

### 2. `set.has()`:

*   This method checks if a specified value exists in a Set object.
*   Pros:
    *   Efficient for large datasets since Sets only store unique values
    *   Fast performance due to the use of hash tables internally
    *   Can be faster than array.includes() for very large arrays
*   Cons:
    *   Requires creating an additional Set object, which can incur overhead in terms of memory allocation and garbage collection
    *   May not be suitable for small or empty datasets

### 3. `in` operator:

*   This method checks if a specified value exists in the array using the `in` keyword.
*   Pros:
    *   Simple to implement
    *   Fast performance since it only needs to access the array's prototype chain
    *   Can be faster than array.includes() for small arrays or when working with objects that have inherited properties from the array's prototype
*   Cons:
    *   May not work correctly in all cases (e.g., when using a custom array implementation)
    *   Can be slower than `set.has()` for very large arrays due to the need to access each element

**Library/ Framework:**

The benchmark script uses JavaScript's built-in data structures and operators. There are no external libraries or frameworks involved.

**Special JS feature/Syntax:**

There is no special JavaScript feature or syntax used in this benchmark. It only relies on standard JavaScript language features.

**Other Alternatives:**

If you're interested in exploring alternative ways to check if an element exists in an array, here are a few options:

*   **Binary Search:** For sorted arrays, binary search can be an efficient way to find an element.
*   **Hash Table Lookups:** If the array is already indexed or has a unique identifier for each element, using a hash table lookup can be faster than linear searches.
*   **Fibonacci Search:** Another alternative method for finding an element in a sorted array is the Fibonacci search algorithm.

Keep in mind that these alternatives may have different performance characteristics depending on the specific use case and data distribution.

Related benchmarks:

set.has vs. array.includes vs in operator (version: 0)

Comparing performance of: includes vs lookup vs in

Created: one year ago by: Guest

Jump to the latest result

includes

lookup

in

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):